A threat-oriented digital twinning methodology and open-source modular twin is introduced for security evaluation of autonomous platforms, translating threat analysis into controllable tests for spoofing, replay, and adversarial ML attacks.
Air force vehicles
5 Pith papers cite this work. Polarity classification is still indexing.
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Bidirectional feedback between physical and virtual systems is the defining property of digital twins, serving as an organizing principle for multi-scale hierarchies in biological and social organization.
A physics-constrained inverse-problem framework identifies graph-based lumped-parameter thermal models from temperature measurements for spacecraft digital-twin applications.
Proposes the CBDT framework as a minimum viable digital twin for CI builds to enable real-time monitoring, ML modeling, and prescriptive optimization of build duration, failures, and flakiness.
An integrated IoT and CNN system detects cracks in additive manufacturing with 99.54% accuracy and supports predictive maintenance via digital twins.
citing papers explorer
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Threat-Oriented Digital Twinning for Security Evaluation of Autonomous Platforms
A threat-oriented digital twinning methodology and open-source modular twin is introduced for security evaluation of autonomous platforms, translating threat analysis into controllable tests for spoofing, replay, and adversarial ML attacks.
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Digital Twins Need Feedback
Bidirectional feedback between physical and virtual systems is the defining property of digital twins, serving as an organizing principle for multi-scale hierarchies in biological and social organization.
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Physics-constrained identification of graph-based thermal networks for spacecraft digital twins
A physics-constrained inverse-problem framework identifies graph-based lumped-parameter thermal models from temperature measurements for spacecraft digital-twin applications.
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Towards Build Optimization Using Digital Twins
Proposes the CBDT framework as a minimum viable digital twin for CI builds to enable real-time monitoring, ML modeling, and prescriptive optimization of build duration, failures, and flakiness.
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IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0
An integrated IoT and CNN system detects cracks in additive manufacturing with 99.54% accuracy and supports predictive maintenance via digital twins.